Adaptive frequency-domain reference noise canceller for multicarrier communications systems

ABSTRACT

A method and apparatus to align data blocks in a data signal and a reference signal to increase cross-correlation between the data signal and the reference signal as compared to the unaligned data and reference signals and cancel interference in the data signal in the frequency-domain under changing conditions and in the presence of the data signal.

TECHNICAL FIELD

This invention relates generally to a multi-carrier communication systemand, in particular, to noise cancellation in a multi-carriercommunication system.

BACKGROUND

A multi-carrier communication system, such as a Discrete Multi-Tone(DMT) system in the various types of Digital Subscriber Line (DSL), forexample, asymmetric digital subscriber line (ADSL) and very high-speeddigital subscriber line (VDSL) systems, carries an information bitstream from a transmitter to a receiver. The information bit stream istypically converted into a sequence of data symbols having a number oftones. Each tone may be a group of one or more frequencies defined by acenter frequency and a set bandwidth. The tones are also commonlyreferred to as sub-carriers or sub-channels. Each tone acts as aseparate communication channel to carry information between a localtransmitter-receiver (transceiver) device and a remote transceiverdevice.

FIG. 1 is a block diagram illustrating a conventional DMT receiver. Achannel equalizer is used to control the spread of the data symbolsafter going through the channel. A cyclic prefix (CP) may be employed insuch systems to simplify channel equalization to minimize a source ofcross channel interference. Generally, if the length of the channelimpulse response is equal to or less than the cyclic prefix length plusone sample, then channel equalization is trivial and perfectequalization can be achieved. The channel can be inverted in thefrequency domain after a discrete Fourier transform (DFT) by a singlecomplex multiply for each sub-channel. This is usually referred to asfrequency-domain equalization (FEQ).

On transmission lines in DMT communication systems, such as ADSL orVDSL, the data signal is generally transmitted differentially.Interference such as radio-frequency interference (RFI), crosstalk andimpulse noise electromagnetically couples into both the common mode andthe differential mode of such transmission lines. In the case of abinder containing multiple transmission lines, such interference maycouple into some or all of the transmission line in the binder and suchnoise may be correlated between lines.

Conventional techniques for reducing differential noise, therebyimproving data rates over the DSL, include use of common-modeinformation. In a traditional DSL system, the common-mode voltage ismeasured, an estimate of the differential-mode interference isconstructed and the interference estimate is subtracted from the desiredsignal.

Traditional cancellation may occur in the time-domain or the frequencydomain. For example, frequency bands containing RFI are band-passfiltered and then subtracted from the differential-mode signal in thetime domain. In the frequency domain, a small set of frequency bins areused to compute and remove an estimate of RFI on a larger number of datacarrying frequency bins. Other conventional systems cancel crosstalk inboth the time domain and the frequency domain by solving a specific setof equations.

However, there are significant drawbacks associated with filtering andsubtracting an interference estimate in the time-domain. For example,training and updating the noise estimation unit is difficult, especiallyin the presence of a data signal. Furthermore, time-domain subtractiontends to result in noise enhancement. A reduction in the power spectraldensity (PSD) of the interference may be achieved over parts of thefrequency band where the interference is strongest, but interference PSDenhancement may occur in other frequency regions, resulting insub-optimal system performance.

Known frequency-domain techniques also have significant limitations.Common-mode interference may not be limited to crosstalk or RFI alone,but may be a combination of the two. There may also be wideband noisefrom sources other than radio transmitters (RFI) or other communicationssystems (crosstalk) that is correlated between the common anddifferential modes. Conventional solutions are suited to target onlycrosstalk or RFI; not both. Also, the interference sources and theirassociated coupling transfer functions will, in general, change overtime. Known cancellers do not have the ability to adapt to thesechanging conditions in the presence of the data signal. Furthermore, ina practical implementation, there are complications and difficultiesassociated with the dynamic range of both the differential-mode andcommon-mode signals. In implementations in which the multi-carriercommunications system is an ADSL or VDSL system, there may be furthercomplications involving interaction of the canceller with On-LineReconfiguration (OLR), Seamless Rate Adaptation (SRA), and bitswap asdefined in the various ADSL and VDSL standards. During such events thetransmitted power and/or the constellation size changes for one or moresub-carriers.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example, and not by wayof limitation, in the figures of the accompanying drawings.

FIG. 1 is a block diagram illustrating a conventional DMT receiver.

FIG. 2 is a block diagram illustrating an embodiment of a discretemulti-tone system.

FIG. 3 is a block diagram illustrating one embodiment of a receiverhaving an adaptive frequency-domain reference noise canceller.

FIG. 4 is a block diagram illustrating an alternative embodiment of areceiver having an adaptive frequency-domain reference noise canceller.

FIG. 5 is a block diagram illustrating a second alternative embodimentof a receiver having an adaptive frequency-domain reference noisecanceller.

FIG. 6 is a flow chart illustrating one embodiment of an interferencecancellation method.

FIG. 7 is a flow chart illustrating one embodiment of a block alignmentadjustment method.

FIG. 8 is a block diagram illustrating one embodiment of a blockaligner.

DETAILED DESCRIPTION

In the following description, numerous specific details are set forth,such as examples of specific commands, named components, connections,number of frames, etc., in order to provide a thorough understanding ofthe present invention. It will be apparent, however, to one skilled inthe art that the present invention may be practiced without thesespecific details. In other instances, well known components or methodshave not been described in detail but rather in a block diagram in orderto avoid unnecessarily obscuring the present invention. Thus, thespecific details set forth are merely exemplary. The specific detailsmay be varied from and still be contemplated to be within the scope ofthe present invention.

Some portions of the description that follow are presented in terms ofalgorithms and symbolic representations of operations on data that maybe stored within a memory and operated on by a processor. Thesealgorithmic descriptions and representations are the means used by thoseskilled in the art to effectively convey their work. An algorithm isgenerally conceived to be a self-consistent sequence of acts leading toa desired result. The acts are those requiring manipulation ofquantities. Usually, though not necessarily, these quantities take theform of electrical or magnetic signals capable of being stored,transferred, combined, compared, and otherwise manipulated. It hasproven convenient at times, principally for reasons of common usage, torefer to these signals as bits, values, elements, symbols, characters,terms, numbers, parameters, or the like.

The following detailed description includes several modules, which willbe described below. These modules may be implemented by hardwarecomponents, such as logic, or may be embodied in machine-executableinstructions, which may be used to cause a general-purpose orspecial-purpose processor programmed with the instructions to performthe operations described herein. Alternatively, the operations may beperformed by a combination of hardware and software.

Embodiments of a method and apparatus are described to cancelinterference in a multi-carrier communications system. In oneembodiment, a data signal and a reference signal are received at areceiver. The reference signal is obtained by measuring a common-mode ordifferential-mode voltage. A block aligner is used to align data blocksin the data and reference signals to increase cross-correlation betweenthe data signal and the reference signal as compared to the unaligneddata and reference signals. The aligned time-domain signals aretransformed to the frequency-domain where interference cancellationoccurs. A tone-by-tone canceller includes a decision feedback mechanismto adapt the canceller under changing conditions in the presence of thedata signal in the frequency-domain.

FIG. 2 is a block diagram illustrating an embodiment of a discretemulti-tone system. The discrete multi-tone system 200, such as a DigitalSubscriber Line (DSL) based network, may have two or more transceivers202 and 204, such as a DSL modem in a set top box. In one embodiment,the set top box may be a stand-alone DSL modem. In one embodiment, forexample, the set top box employs a DSL modem along with other mediacomponents to combine television (Internet Protocol TV or satellite)with broadband content from the Internet to bring the airwaves and theInternet to an end user's TV set. Multiple carrier communicationchannels may communicate a signal to a residential home. The home mayhave a home network, such as an Ethernet. The home network may eitheruse the multiple carrier communication signal directly, or convert thedata from the multiple carrier communication signal. The set top box mayalso include, for example, an integrated Satellite and DigitalTelevision Receiver, High-Definition Digital Video Recorder, DigitalMedia Server and other components.

The first transceiver 202, such as a Discrete Multi-Tone transmitter,transmits and receives communication signals from the second transceiver204 over a transmission medium 206, such as a telephone line. Otherdevices such as telephone 208 may also connect to this transmissionmedium 206. An isolating filter 210 generally exists between thetelephone 208 and the transmission medium 206. A training period occurswhen initially establishing communications between the first transceiver202 and a second transceiver 204.

The discrete multi-tone system 200 may include a central office,multiple distribution points, and multiple end users. The central officemay contain the first transceiver 202 that communicates with the secondtransceiver 204 at an end user's location.

Each transmitter portion 217, 219 of the transceivers 202, 204,respectively, may transmit data over a number of mutually independentsub-channels i.e., tones. In a DMT communication system, data samples oneach tone are represented as one of a set of finite number of points ina two-dimensional (2D) Quadrature Amplitude Modulation (QAM)constellation. The transmitted data in a multi-carrier system is usuallyrepresented by a point from a constellation of a finite set of possibledata points, regularly distributed over a two dimensional space. Eachsub-channel carries only a certain portion of data through QAM of thesub-carrier. The number of information bits loaded on each tone and thesize of corresponding QAM constellation may potentially vary from onetone to another and depend generally on the relative power of signal andnoise at the receiver. When the characteristics of signal and noise areknown for all tones, a bit-loading algorithm may determine the optimaldistribution of data bits and signal power amongst sub-channels. Thus, atransmitter portion 217, 219 of the transceivers 202, 204 modulates eachsub-carrier with a data point in a QAM constellation.

It should be noted that embodiments of the present invention aredescribed below in reference to receiver 316, which represents oneembodiment of receiver 216, for ease of discussion, and that receiver218 may operate in a similar manner as described below for receiver 316.

FIG. 3 is a block diagram illustrating one embodiment of a receiverhaving an adaptive frequency-domain reference noise canceller. In thisembodiment, receiver 316 includes time domain filtering modules 321,322, block aligner 323, cyclic extension (CE) removal andserial-to-parallel module 324, sample drop and serial-to-parallel module325, fast Fourier transform (FFT) modules 326, 327, channel flatteningfrequency-domain equalizer (CF-FEQ) module 328, bin power normalizationmodule 329, adders 330, 333, interference estimator module 331, gaininversion and constellation scaling (GICS) module 332, and constellationdecision logic module 334. Additional modules and functionality mayexist in the receiver 316 that are not illustrated so as not to obscurean understanding of embodiments of the present invention. It should benoted that the operations of one or more modules may be incorporatedinto or integrated with other modules.

In one embodiment, receiver 316 is implemented in a DMT communicationssystem operating over a twisted-pair communications channel. N is avariable representing the number of tones used in the multi-carriercommunication receiver. The communications system may operate in thepresence of RFI, crosstalk and other interference. In this embodiment,received samples of a differential-mode primary data signal sent overthe twisted pair are provided to a first time-domain filtering module321. Additionally, a sampled reference signal is received and providedto a second time-domain filtering module 322. The reference signal isobtained by sampling the common-mode signal of the same twisted-pair asthe primary data signal. In an alternative embodiment, the referencesignal is obtained by sampling the differential mode interference from asecond twisted-pair that is not used for data transmission. In anotheralternative embodiment, the primary data signal is obtained by samplingthe differential voltage of a copper pair in a twisted copper quad andthe reference signal is obtained by sampling the differential-modeinterference from the other two wires of the twisted quad.

In this embodiment, receiver 316 is configured to operate independentlyof the source of the reference signal. A data signal and a referencesignal are received and undergo digital time-domain filtering at modules321 and 322 respectively. Receiver 316 further includes a block alignermodule 323. Block aligner module 323 adjusts the relative alignment ofthe 2N-sample blocks of the primary data signal and the reference signalas needed. The block aligner module 323 may be implemented withsample-dropping capability, by programming delay First in, First out(FIFO) buffers, or by adjusting the group delay of programmable finiteimpulse response (FIR) filters. The block aligner module 323 aligns theblocks such that the cross correlation of the reference signal and theprimary line interference signal is increased as compared to the crosscorrelation of the unaligned data and reference signals. For example,the increase in cross-correlation may be in a range of approximately 50percent to over an order of magnitude. In one embodiment, the blocks arealigned such that the cross-correlation is maximized. Block alignermodule 323 will be described further below, with respect to FIG. 8.

A first output of block aligner module 323 provides the aligned datasignal to cyclic extension (CE) removal and serial-to-parallel module324. A second output of block aligner module 323 provides the alignedreference signal to sample drop and serial-to-parallel module 325.Modules 324 and 325 serve to remove samples corresponding to any cyclicextension that may have been added to the data stream at the transmitteras well as convert the serial sample stream in to chunks which may beoperated on in parallel.

The data signal and reference signal undergo 2N-point discrete Fouriertransforms (DFT). In this embodiment, the DFT is computed efficiently bymeans of a fast Fourier transform (FFT) at FFT modules 326 and 327. Thetime-domain samples of both the data signal and the reference signal areprovided to FFT modules 326 and 327 which convert the samples intofrequency-domain symbols to be used by the canceller. The output of FFTmodule 326 for the data signal is sent to a channel flatteningfrequency-domain equalizer (CF-FEQ) module 328. The CF-FEQ modulenormalizes the phase and power on each frequency bin of the data signal.In a traditional DMT system, at the output of the FFT, each frequencybin of the data signal undergoes an FEQ multiply that inverts thechannel attenuation and phase rotation, inverts the fine gain adjustmentvalue assigned to the bin, and adjusts for the constellation size. Theresult is such that the FEQ output is scaled to an integer grid fordecoding. In this embodiment of the present invention, the traditionalFEQ is split into a CF-FEQ module 328 and a gain inversion andconstellation scaling (GICS) module 332. The two stage approach allowsthe data signal from the output of FFT module 326 to be normalized forcomputationally efficient removal of interference using integerarithmetic. It also decouples on-line reconfiguration (OLR), seamlessrate adaptation (SRA) and bitswap from the reference noise canceller.That is, the reference noise canceller taps do not need to change duringor after such an event.

The output of FFT module 327 for the reference signal undergoes ascaling stage in which the power on each frequency bin of the referencesignal is normalized. The bin-power normalization module 329 receivesthe output of FFT module 327 and corrects amplitude and phase distortionin the reference signal. The bin-power normalization module 329 producesa normalized reference channel output signal Yref.

The normalized reference channel output signal Yref is provided to aninterference estimator module 331. Interference estimator module 331multiplies the reference signal Yref by a single complex tap for eachfrequency bin thus forming an estimate of the interference in thedifferential-mode signal for each bin. This estimate is subtracted fromthe normalized primary channel output signal Y provided by the CF-FEQmodule 328. The subtraction is performed by adder 330 and results in acanceller output signal Yc. The canceller output signal Yc is providedto an input of the GICS module 332.

GICS module 332 adjusts the signal for per-bin gain and constellationsize. The GICS module 332 produces an output signal Xhat which isprovided to an input of a constellation decision logic module 334. Inthe constellation decision logic module 334, the signal Xhat undergoesconstellation decoding where constellation decisions are formed. Theconstellation decision logic module 334 may include a trellis decoder ora simple un-coded constellation decoder or slicer. Constellationdecision logic module 334 produces a constellation decision signal X.The constellation decision signal X is subtracted from the GICS moduleoutput signal Xhat to form a decision error estimate E. The subtractionis performed by adder 333. The decision error estimate E is used toadaptively update the canceller taps in the interference estimatormodule 331. In one embodiment, a least-mean-square (LMS) algorithm isused to update the taps. In alternative embodiments, other algorithmsmay be used to update the taps such as a recursive least square (RLS)algorithm, a gradient computation, or other algorithm. The structure ofreceiver 316 allows the canceller to adapt under changing conditions,such as interference sources and their associated coupling transferfunctions, and effectively cancel interference in the presence of theactual data signal.

FIG. 4 is a block diagram illustrating an alternative embodiment of areceiver 416 having an adaptive frequency-domain reference noisecanceller. In this embodiment, the CF-FEQ module 328 of FIG. 3 isremoved and the GICS module 332 of FIG. 3 is replaced with FEQ module435. FEQ module 435 receives the canceller output signal Yc at an inputand provides the decoder input signal Xhat to constellation decisionlogic module 334. The canceller output signal Yc is obtained bysubtracting the interference estimate directly from the primary channeloutput Y of FFT module 326. The reference signal is processed in thesame manner as described above with respect to FIG. 3.

FIG. 5 is a block diagram illustrating a second alternative embodimentof a receiver having an adaptive frequency-domain reference noisecanceller. In this embodiment, the CF-FEQ module 328 of FIG. 3 isreplaced with FEQ module 536 and GICS module 332 of FIG. 3 is removed.FEQ module 536 receives the output of FFT module 326 at an input andprovides an FEQ output signal Y to adder 330. Bin power normalizationmodule 329 of FIG. 3 has also been removed in this embodiment. Thereference channel output Yref of the FFT module 327 is directlymultiplied by a single complex tap to form an interference estimate atinterference estimator module 331. The interference estimate issubtracted from the FEQ output signal Y at adder 330 and the cancelleroutput Y is provided directly to the constellation decision logic module334.

FIG. 6 is a flow chart illustrating one embodiment of an interferencecancellation method 600. The process 600 may be performed by processinglogic that comprises hardware, firmware, software, or a combinationthereof. In one embodiment, process 600 is performed by the receiver 316of FIG. 3.

Referring to FIG. 6, interference cancellation method 600 reduces theinterference in a data signal in a multi-carrier communications system.At block 610, method 600 aligns data blocks from a received data signaland a reference signal to increase cross correlation between the datasignal and the reference signal as compared to the unaligned data andreference signals. The block alignment process will be discussed furtherbelow with respect to FIG. 7.

At block 620, method 600 drops unneeded samples corresponding to thecyclic extension of the data signal from the aligned data and referencesignals. Method 600 also removes any cyclic extension that may have beenadded to the data stream at the transmitter as well as converts theserial sample stream in to chunks which may be operated on in parallel.At block 630, method 600 transforms the data and reference signals fromthe time-domain to the frequency-domain. The transformation may beaccomplished with the use of a discrete Fourier transform (DFT). In oneembodiment, the DFT is performed by FFT modules 326 and 327 of FIG. 3.

At block 640, method 600 normalizes the power on each frequency bin ofthe data and reference signals. Method 600 corrects any amplitude andphase distortion in the signal to enable efficient noise cancellation.At block 650, the data signal undergoes a constellation decision logicstage where constellation decisions are formed. The output of theconstellation decision logic is subtracted from the input to form anerror estimate. The error estimate is used to adaptively updatecanceller taps at block 660. In one embodiment, a least-mean-square(LMS) algorithm is used to update the taps. In alternative embodiments,other algorithms may be used to update the taps such as a recursiveleast square (RLS) algorithm, a gradient computation, or otheralgorithm.

At block 670, method 600 multiplies the transformed reference signal bya single complex tap for each of one or more frequency bins of thereference signal. The multiplication results in an estimate of theinterference in the data signal. At block 680, method 600 subtracts theinterference estimate from the data signal. The subtraction results in acanceller output signal which is then applied to an input theconstellation decision logic and method 600 continues at block 650 withthe new input. In this manner, method 600 is able to adaptively updatethe interference canceller with an interference estimate to cancelchanging sources of interference during data transmission.

FIG. 7 is a flow chart illustrating one embodiment of a block alignmentadjustment method 700. The process 700 may be performed by processinglogic that comprises hardware, firmware, software, or a combinationthereof. In one embodiment, process 700 is performed by the blockaligner 323 of FIG. 3.

Referring to FIG. 7, block alignment adjustment method 700 enablesalignment of data blocks from at least a received data signal and areference signal to increase cross correlation between the data signaland the reference signal as compared to the unaligned data and referencesignals. Alignment of the data blocks allows for the canceller toachieve optimal noise cancellation. At block 710, method 700 sets theblock alignment to a default value. In one embodiment, the default valuemay be zero offset in both the data signal and the reference signal.

At block 720, method 700 collects 2N time-domain samples from each ofthe time domain signal and the reference signal. In one embodiment, thecollection of each of the two sets of 2N samples begins at the sameabsolute time. This results in the 2N-sample blocks of the data signaland reference signal being roughly-aligned.

At block 730, method 700 performs cross-correlation of the data andreference signals and computes a peak offset value. Block alignment finetuning is performed by using the cross-correlation of the interferenceon the data and reference signals. The measurement occurs when the datasignal is not present, such as before modem training commences or at atime during modem training when the far-end transmitter is quiet. Afterdual 2N-sample blocks are captured at block 720, the cross correlationis computed as

$\begin{matrix}{{\left( {y*y_{{ref}\;}} \right)\lbrack n\rbrack} = {\sum\limits_{j\;}^{\;}{{y\lbrack j\rbrack}*y_{ref}*\left\lbrack {n + j} \right\rbrack}}} & (1)\end{matrix}$

where y is a block of 2N samples from the data signal in the time-domainduring a quiet period, y_(ref) is the corresponding block of 2N samplesfrom the reference signal in the time-domain during the same timeperiod, n is the peak offset between the data and reference signals andj is a counting index. The offset is found by determining the values ofn for which the cross correlation (y*y_(ref))[n] is greater than whenthere is no offset (i.e. n=0). In one embodiment method 700 maydetermine the value of n for which the cross correlation is a maximum. Arange of values for n may result in increased cross correlation, howeveras the values become nearer the value which results in maximumcross-correlation, the efficiency of the interference cancellingincreases. Method 700 selects one value of n to use as the offset in theblock aligner.

At block 740, method 700 makes a determination as to whether theselected value of n is greater or less than zero. If n is greater thanzero, method 700 proceeds to block 750. At block 750, method 700 adjuststhe block alignment by the offset n samples. In one embodiment, method700 increases the delay in the data signal by n samples and in analternative embodiment, method 700 decreases the delay in the referencesignal by n samples. If n is less than zero, method 700 proceeds toblock 760. At block 760, method 700 adjusts the block alignment by theoffset, n samples. In one embodiment, method 700 increases the delay inthe reference signal by (−n) samples and in an alternative embodiment,method 700 decreases the delay in the data signal by (−n) samples. Afterthe block alignment has been adjusted at either block 750 or 760, method600 ends.

FIG. 8 is a block diagram illustrating one embodiment of a block aligner823. The block aligner 823 includes two D-sample delay FIFO buffers 883,893. A first FIFO buffer 883 is in the primary data signal path and asecond FIFO buffer 893 is in the reference signal path. If the delaythrough both time-domain filtering blocks 321, 322 is equivalent, andthe Serial-to-Parallel blocks 324, 325 are synchronized such that samplecollection for each block begins at the same time on both channels, thenthe block aligner 823 in this form allows for a plus or minus D-samplefine-tuning delay adjustment between the primary and reference paths. Inan alternative embodiment, finite impulse response (FIR) filters areused in place of FIFO buffers 883, 893. Block aligner 823 aligns theblocks of the data and reference signals such that there is an increasein the cross-correlation between the data signal and the referencesignal as compared to the unaligned data and reference signals.

In one embodiment, the methods described above may be embodied onto amachine-readable medium. A machine-readable medium includes anymechanism that provides (e.g., stores and/or transmits) information in aform readable by a machine (e.g., a computer). For example, amachine-readable medium includes read only memory (ROM); random accessmemory (RAM); magnetic disk storage media; optical storage media; flashmemory devices; DVD's, or any type of media suitable for storingelectronic instructions. The information representing the apparatusesand/or methods stored on the machine-readable medium may be used in theprocess of creating the apparatuses and/or methods described herein.

While some specific embodiments of the invention have been shown theinvention is not to be limited to these embodiments. The invention is tobe understood as not limited by the specific embodiments describedherein, but only by the scope of the appended claims.

1. A method comprising: receiving a data signal and a reference signal;and aligning data blocks in the data signal with data blocks in thereference signal to increase cross-correlation between the data signaland the reference signal as compared to the unaligned data and referencesignals.
 2. The method of claim 1, wherein aligning the data blockscomprises introducing a first delay into the data signal and introducinga second delay into the reference signal.
 3. The method of claim 2,wherein introducing a first delay comprises programming a firstprogrammable delay First in, First out (FIFO) buffer and introducing asecond delay comprises programming second programmable delay FIFObuffer.
 4. The method of claim 2, wherein introducing a first delay anda second delay comprises adjusting the group delay of a firstprogrammable finite impulse response (FIR) filter and a secondprogrammable FIR filter.
 5. The method of claim 3 further comprising:generating an interference estimate by multiplying the aligned referencesignal by a single complex tap for each of one or more frequency bins ofthe reference signal; and subtracting the interference estimate from thealigned data signal.
 6. An apparatus comprising: a block alignerconfigured to align data blocks in a data signal received from a dataline with data blocks in a reference signal received from a referencelineto increase cross-correlation between the data signal and thereference signal as compared to the unaligned data and referencesignals.
 7. The apparatus of claim 6, wherein the block alignercomprises a first delay module coupled to the data line and configuredto introduce a first delay into the data signal and a second delaymodule coupled to the reference line and configured to introduce asecond delay into the reference signal.
 8. The apparatus of claim 7,wherein the first and second delay modules comprise programmable delayFirst in, First out (FIFO) buffers.
 9. The apparatus of claim 7, whereinthe first and second delay modules comprise programmable finite impulseresponse (FIR) filers.
 10. The apparatus of claim 7, further comprising:a tone-by-tone canceller coupled to the block aligner and configured tooperate in the frequency domain and cancel interference in the datasignal.
 11. A method comprising: generating an interference estimate fora received data signal; and adaptively updating an interferencecanceller with the interference estimate to cancel changing sources ofinterference during data transmission.
 12. The method of claim 11,wherein generating an interference estimate comprises: generating anerror estimate in the data signal; adaptively updating canceller tapswith the error estimate; and multiplying a reference signal by a singlecomplex canceller tap for each of one or more frequency bins of thereference signal.
 13. The method of claim 12, wherein generating anerror estimate comprises subtracting an output of a constellationdecision logic module from an input of the constellation decision logicmodule.
 14. The method of claim 12, wherein adaptively updating thecanceller tap comprises using the error estimate in a least-mean-squarealgorithm.
 15. The method of claim 12, wherein adaptively updating thecanceller tap comprises using the error estimate in a recursive leastsquare algorithm.
 16. The method of claim 11, wherein adaptivelyupdating the interference canceller comprises subtracting theinterference estimate from the data signal.
 17. The method of claim 16,further comprising: aligning blocks of the data signal with blocks of areference signal to increase cross-correlation between the data signaland the reference signal as compared to the unaligned data and referencesignals.
 18. An apparatus comprising: a tone-by-tone canceller operatingin the frequency domain, configured to reduce interference in a datasignal.
 19. The apparatus of claim 18, wherein the tone-by-tonecanceller comprises: a constellation decision logic module to performconstellation decoding; a first adder coupled to the constellationdecision logic module and configured to subtract an output of theconstellation decision logic module from an input of the constellationdecision logic module to form an error estimate; an interferenceestimator module coupled to the first adder and configured to receivethe error estimate; and a second adder coupled to the interferenceestimator module and configured to subtract the interference estimatefrom the data signal.
 20. The apparatus of claim 19, wherein theconstellation decision logic module comprises a trellis decoder.
 21. Theapparatus of claim 19, wherein the constellation decision logic modulecomprises an un-coded constellation decoder.
 22. The apparatus of claim19, further comprising: a block aligner coupled to the tone-by-tonecanceller, wherein the block aligner is configured to align data blocksin the data signal and a reference signal to increase cross-correlationbetween the data signal and the reference signal as compared to theunaligned data and reference signals.
 23. A method comprising: aligningblocks of a received data signal with blocks of a received referencesignal to increase cross-correlation between the data signal and thereference signal as compared to the unaligned data and referencesignals; and canceling interference in the data signal in the frequencydomain.
 24. The method of claim 23, further comprising: droppingunneeded samples corresponding to a cyclic extension of the data signalfrom the aligned data and reference signals.
 25. The method of claim 24,further comprising: transforming the aligned data and reference signalsfrom the time-domain to the frequency-domain.
 26. The method of claim25, further comprising: normalizing a power of one or more frequencybins of both the transformed data signal and the transformed referencesignal.
 27. The method of claim 26, further comprising: generating aninterference estimate by multiplying the transformed reference signal bya single complex tap for each of the one or more frequency bins of thereference signal.
 28. The method of claim 27, wherein cancelinginterference in the data signal comprises subtracting the interferenceestimate from the transformed data signal.
 29. An apparatus comprising:a block aligner configured to align data blocks in a data signal and areference signal to increase cross-correlation between the data signaland the reference signal as compared to the unaligned data and referencesignals; and a tone-by-tone canceller coupled to the block aligner, thecanceller operating in the frequency domain to cancel interference inthe data signal.
 30. The apparatus of claim 29, wherein the blockaligner comprises a first delay module configured to introduce a firstdelay into the data signal and a second delay module configured tointroduce a second delay into the reference signal.
 31. The apparatus ofclaim 30, wherein the tone-by-tone canceller comprises: a constellationdecision logic module to perform constellation decoding; a first addercoupled to the constellation decision logic module and configured tosubtract an output of the constellation decision logic module from aninput of the constellation decision logic module to form an errorestimate; a interference estimator module coupled to the first adder andconfigured to receive the error estimate; and a second adder coupled tothe interference estimator module and configured to subtract theinterference estimate from the data signal.
 32. The apparatus of claim31, further comprising: a cyclic extension removal andserial-to-parallel module coupled to the block aligner and configured toremove a number of redundant samples from the data signal; and a sampledrop and serial-to-parallel module coupled to the block aligner andconfigured to remove a same number of samples from the reference signalas were removed from the data signal.
 33. The apparatus of claim 32,further comprising: a first fast Fourier transform (FFT) module coupledto the cyclic extension and serial-to-parallel module to transform thedata signal from the time-domain to the frequency-domain; and a secondFFT module coupled to the sample drop and serial-to-parallel module totransform the reference signal from the time-domain to thefrequency-domain.
 34. The apparatus of claim 33, further comprising: achannel flattening frequency domain equalizer (CF-FEQ) module coupled tothe first FFT module and configured to receive an output of the firstFFT module and provide an output to an adder; a gain inversion andconstellation scaling (GICS) module coupled to the second adder andconfigured to receive an output of the adder; and a bin powernormalization module coupled to the second FFT module and configured toreceive an output of the second FFT module.
 35. The apparatus of claim34, wherein the GICS module is further configured to decouple on-linereconfiguration (OLR), seamless rate adaptation (SRA) and bitswap fromthe tone-by-tone canceller.
 36. An apparatus, comprising: means forreceiving a data signal and a reference signal; and means for aligningdata blocks in the data signal with data blocks in the reference signalto maximize cross-correlation between the data signal and the referencesignal.
 37. The apparatus of claim 36, wherein the means for receivingcomprises means for performing time-domain filtering of the data signaland the reference signal.
 38. The apparatus of claim 36, furthercomprising: means for collecting 2N time-domain samples of the datasignal and the reference signal.
 39. The apparatus of claim 38, furthercomprising: means for performing cross-correlation of the data signaland the reference signal and computing a peak offset value of thesamples.
 40. The apparatus of claim 39, further comprising: means forintroducing a first delay into the data signal and a second delay intothe reference signal.
 41. The apparatus of claim 40, further comprising:means for generating an interference estimate for the data signal; andmeans for adaptively updating an interference canceller with theinterference estimate during data transmission.